The specific aims are: 1) To compare frequency of complex ventricular ectopy, events of sudden cardiac arrest, and survival rate between randomized treatment and control groups of persons at risk of sudden cardiac arrest before and after self-management/biofeedback therapy over a period of two years. A comparison of mortality rates and recurrent events of sudden cardiac arrest will also be made between the treatment group and all the subjects in two large registries of sudden cardiac arrests/deaths. 2) To compare the non-spectral and power spectral measurements of heart rate variability (HRV), perceived control, affective states (i.e., depression, anxiety, etc.), psychosocial adaptation, functional status, and quality of life between randomized treatment and control groups of persons at risk of sudden cardiac arrest before and after self-management/biofeedback therapy over a period of one year. 3) To describe the relationships between the aforementioned variables at the same points in time (i.e., cross-sectional periods). 4) To describe the normative values of the non-spectral and power spectral measurements of HRV in a group of persons without cardiac disease and compare these values with persons at risk of sudden cardiac arrest. The design is a randomized, two-group, experimental, repeated measures, longitudinal study. The sample size is 65 in each of the treatment at exit, and at follow-up times at 6 and 12 months. Mortality and recurrent events of sudden cardiac arrest will be tracked at 2-year follow-up through two registries. Forty subjects without cardiac disease will be studied to describe normative values of HRV. The biobehavioral interventions: self-management therapy is focused on training sudden cardiac survivors to cognitively alter their cognitive/affective states and increase HRV by use of the respiratory sinus arrhythmia (that is, heart rate will increase and decrease in phase with respirations as tidal volume is increased and breathing rate is decreased). The respiratory sinus arrhythmia is primarily parasympathetic. Power spectral analysis of HRV enables separation of the parasympathetic and sympathetic components. Statistical analysis includes log-rank test and Cox proportional hazards regression model, analysis of variance for repeated measures, analysis of covariance, regression analysis, and t-tests.